class_docstr: Calculates the values of a set of features for given instance ids.
code: def _calculate_identity_features(
      self, features, df, _df_trie, progress_callback
  ):
      for f in features:
          assert f.get_name() in df.columns, (
              'Column "%s" missing frome dataframe' % f.get_name()
          )
  
      progress_callback(len(features) / float(self.num_features))
  
      return df
  
imports: from datetime import datetime
  from functools import partial
  import numpy
  import pandas
  import pandas.api.types
  from featuretools.entityset.relationship import RelationshipPath
  from featuretools.exceptions import UnknownFeature
  from featuretools.feature_base import AggregationFeature, DirectFeature, GroupByTransformFeature, IdentityFeature, TransformFeature
  from featuretools.utils import Trie
  from featuretools.utils.gen_utils import Library, get_relationship_column_id, import_or_none, is_instance
label_desc: Use image node_id 8 for calling the FeatureSetCalculator obj's underlying member method code with example usage: obj._calculate_identity_features(features, df, _df_trie, progress_callback) and returns: df